Javascript must be enabled to continue!
Inertial Sensor Self-Calibration Module Using Attitude Heading And Reference System For Autonomous Underwater Vehicle Navigation
View through CrossRef
This research addresses the complex task of enhancing navigation accuracy in Autonomous Underwater Vehicles (AUVs), a self-propelled robotic system used for ocean exploration, environmental monitoring, and underwater interventions. A core component of AUV navigation is an Inertial Measurement Unit (IMU), a sensor suite that tracks orientation and motion by measuring accelerations and angular rates. However, the IMU is highly susceptible to noise interference, which degrades accuracy and reliability. To address these challenges, this study introduces an innovative Inertial Sensor Self-Calibration Module that dynamically adjusts calibration parameters in real time, thereby compensating for sensor drift and inaccuracies. The research further conducts a comparative analysis of several calibration and filtering techniques integrated into the AUV's Inertial Navigation System (INS), including Magnetic Calibration, the Extended Kalman Filter (EKF), the EKF with Measurement Noise, the EKF with Process Noise, and the Attitude and Heading Reference System (AHRS) Filter. Among these, the AHRS filter demonstrated superior precision, achieving the lowest average error of 1.06 degrees with a standard deviation of 0.345 degrees in angle measurements, an improvement of up to 97.81% compared to raw data. These findings highlight the effectiveness of the AHRS filter in improving navigation accuracy in complex underwater environments. The insights gained from this research not only deepen the understanding of noise impact and sensor calibration in AUV systems but also pave the way for future innovations in oceanic exploration, environmental monitoring, and underwater interventions.
ABSTRAK: Kajian ini adalah berkenaan menangani tugas kompleks meningkatkan ketepatan navigasi Kenderaan Bawah Air Autonomi (AUV), iaitu sistem robotik berkuasa sendiri digunakan bagi penerokaan lautan, pemantauan alam sekitar, dan intervensi bawah air. Komponen utama navigasi AUV bergantung pada Unit Pengukuran Inersia (IMU), iaitu rangkaian pengesan orientasi dan pergerakan dengan mengukur pecutan dan kadar sudut. Namun, IMU sangat terdedah kepada gangguan bunyi, di mana ianya mengurangkan ketepatan dan kebolehpercayaan. Oleh itu, kajian ini memperkenalkan Modul Kalibrasi Diri Pengesan Inersia yang inovatif, iaitu secara dinamik menyesuaikan parameter kalibrasi pada masa nyata, secara efektif mengimbangi hanyutan sensor dan ketidaktepatan. Kajian ini juga membuat analisis perbandingan beberapa teknik kalibrasi dan penapisan yang diintegrasikan pada Sistem Navigasi Inersia (INS) AUV, termasuk Kalibrasi Magnetik, Penapis Kalman Lanjutan (EKF), EKF dengan Bunyi Pengukuran, EKF dengan Bunyi Proses, dan Penapis Sistem Rujukan Sikap dan Haluan (AHRS). Antara teknik-teknik ini, penapis AHRS menunjukkan ketepatan terbaik, dengan ralat purata terendah iaitu 1.06 darjah dan sisihan piawai pengukuran sudut 0.345 darjah dan peningkatan sehingga 97.81% berbanding data mentah. Penemuan ini menunjukkan keberkesanan penapis AHRS dalam meningkatkan ketepatan navigasi pada persekitaran bawah air yang kompleks. Dapatan kajian ini bukan sahaja memperdalam pemahaman tentang kesan bunyi dan kalibrasi pengesan dalam sistem AUV, tetapi turut membuka ruang terhadap inovasi masa depan dalam penerokaan lautan, pemantauan alam sekitar, dan intervensi bawah air.
Title: Inertial Sensor Self-Calibration Module Using Attitude Heading And Reference System For Autonomous Underwater Vehicle Navigation
Description:
This research addresses the complex task of enhancing navigation accuracy in Autonomous Underwater Vehicles (AUVs), a self-propelled robotic system used for ocean exploration, environmental monitoring, and underwater interventions.
A core component of AUV navigation is an Inertial Measurement Unit (IMU), a sensor suite that tracks orientation and motion by measuring accelerations and angular rates.
However, the IMU is highly susceptible to noise interference, which degrades accuracy and reliability.
To address these challenges, this study introduces an innovative Inertial Sensor Self-Calibration Module that dynamically adjusts calibration parameters in real time, thereby compensating for sensor drift and inaccuracies.
The research further conducts a comparative analysis of several calibration and filtering techniques integrated into the AUV's Inertial Navigation System (INS), including Magnetic Calibration, the Extended Kalman Filter (EKF), the EKF with Measurement Noise, the EKF with Process Noise, and the Attitude and Heading Reference System (AHRS) Filter.
Among these, the AHRS filter demonstrated superior precision, achieving the lowest average error of 1.
06 degrees with a standard deviation of 0.
345 degrees in angle measurements, an improvement of up to 97.
81% compared to raw data.
These findings highlight the effectiveness of the AHRS filter in improving navigation accuracy in complex underwater environments.
The insights gained from this research not only deepen the understanding of noise impact and sensor calibration in AUV systems but also pave the way for future innovations in oceanic exploration, environmental monitoring, and underwater interventions.
ABSTRAK: Kajian ini adalah berkenaan menangani tugas kompleks meningkatkan ketepatan navigasi Kenderaan Bawah Air Autonomi (AUV), iaitu sistem robotik berkuasa sendiri digunakan bagi penerokaan lautan, pemantauan alam sekitar, dan intervensi bawah air.
Komponen utama navigasi AUV bergantung pada Unit Pengukuran Inersia (IMU), iaitu rangkaian pengesan orientasi dan pergerakan dengan mengukur pecutan dan kadar sudut.
Namun, IMU sangat terdedah kepada gangguan bunyi, di mana ianya mengurangkan ketepatan dan kebolehpercayaan.
Oleh itu, kajian ini memperkenalkan Modul Kalibrasi Diri Pengesan Inersia yang inovatif, iaitu secara dinamik menyesuaikan parameter kalibrasi pada masa nyata, secara efektif mengimbangi hanyutan sensor dan ketidaktepatan.
Kajian ini juga membuat analisis perbandingan beberapa teknik kalibrasi dan penapisan yang diintegrasikan pada Sistem Navigasi Inersia (INS) AUV, termasuk Kalibrasi Magnetik, Penapis Kalman Lanjutan (EKF), EKF dengan Bunyi Pengukuran, EKF dengan Bunyi Proses, dan Penapis Sistem Rujukan Sikap dan Haluan (AHRS).
Antara teknik-teknik ini, penapis AHRS menunjukkan ketepatan terbaik, dengan ralat purata terendah iaitu 1.
06 darjah dan sisihan piawai pengukuran sudut 0.
345 darjah dan peningkatan sehingga 97.
81% berbanding data mentah.
Penemuan ini menunjukkan keberkesanan penapis AHRS dalam meningkatkan ketepatan navigasi pada persekitaran bawah air yang kompleks.
Dapatan kajian ini bukan sahaja memperdalam pemahaman tentang kesan bunyi dan kalibrasi pengesan dalam sistem AUV, tetapi turut membuka ruang terhadap inovasi masa depan dalam penerokaan lautan, pemantauan alam sekitar, dan intervensi bawah air.
Related Results
Dynamic stochastic modeling for inertial sensors
Dynamic stochastic modeling for inertial sensors
Es ampliamente conocido que los modelos de error para sensores inerciales tienen dos componentes: El primero es un componente determinista que normalmente es calibrado por el fabri...
Continuous self‐calibration of platform inertial navigation system based on attitude quaternion model
Continuous self‐calibration of platform inertial navigation system based on attitude quaternion model
This study focuses on the continuous self‐calibration of platform inertial navigation system. Since the estimate accuracy of inertial platform error coefficients would be reduced b...
Accurate Integrated Navigation Method Based on Medium Precision Strapdown Inertial Navigation System
Accurate Integrated Navigation Method Based on Medium Precision Strapdown Inertial Navigation System
A method of accurate integrated navigation for high-altitude aerocraft by medium precision strapdown inertial navigation system (SINS), star sensor, and global navigation satellite...
GNSS/IMU integrated navigation heading angle enhancement algorithm based on dual-antenna TDCP
GNSS/IMU integrated navigation heading angle enhancement algorithm based on dual-antenna TDCP
In the integrated navigation system of Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU), attitude estimation, especially accurate estimation of heading...
Heading Toward a Safer Future? An Exploration of Elite Male Footballers' Perceptions Toward Heading and the Heading Guidelines in England
Heading Toward a Safer Future? An Exploration of Elite Male Footballers' Perceptions Toward Heading and the Heading Guidelines in England
Objective:
To explore perceptions of professional male footballers from an English Premier League club on heading in football and the Football Association's (FA...
Emerging underwater survey technologies: A review and future outlook
Emerging underwater survey technologies: A review and future outlook
Emerging underwater survey technologies are revolutionizing the way we explore and understand the underwater world. This review examines the latest advancements in underwater surve...
A novel electromagnetic actuator in an inductive power transmission system for autonomous underwater vehicle
A novel electromagnetic actuator in an inductive power transmission system for autonomous underwater vehicle
Autonomous underwater vehicle is a class of intelligent robots, which has been widely used in ocean observatory. Inductive power transmission is a good way to supply power and exte...
Vehicle Theft Detection and Locking System using GSM and GPS
Vehicle Theft Detection and Locking System using GSM and GPS
A vehicle tracking system is very useful for tracking the movement of a vehicle from any location at any time. An efficient vehicle tracking system is designed and implemented for ...

